[GH-PAGES] Updated website

master/.buildinfo

@@ -1,4 +1,4 @@
 # Sphinx build info version 1
 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: a0c94a33d2796e4f15c0381a109b0531
+config: ae6382d0c6dcb078734471a10c08ed2c
 tags: 645f666f9bcd5a90fca523b33c5a78b7

master/_sources/getting-started/tutorials/01-vector-add.rst.txt

@@ -235,17 +235,17 @@ We can now run the decorated function above. Pass `print_data=True` to see the p
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     2       16384.0   38.400001   38.400001
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     4       65536.0  127.999995  127.999995
     5      131072.0  219.428568  219.428568
     6      262144.0  341.333321  341.333321
     7      524288.0  472.615390  472.615390
     8     1048576.0  614.400016  614.400016
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+    9     2097152.0  722.823517  722.823517
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     11    8388608.0  812.429770  812.429770
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+    13   33554432.0  842.004273  842.906750
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     15  134217728.0  849.737435  850.656574
 
@@ -255,7 +255,7 @@ We can now run the decorated function above. Pass `print_data=True` to see the p
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 1 minutes  42.464 seconds)
+   **Total running time of the script:** ( 1 minutes  26.773 seconds)
 
 
 .. _sphx_glr_download_getting-started_tutorials_01-vector-add.py:

master/_sources/getting-started/tutorials/02-fused-softmax.rst.txt

@@ -278,17 +278,17 @@ We will then compare its performance against (1) :code:`torch.softmax` and (2) t
 
     softmax-performance:
               N      Triton  Torch (native)  Torch (jit)
-    0     256.0  512.000001      512.000001   186.181817
+    0     256.0  546.133347      512.000001   188.321838
     1     384.0  614.400016      585.142862   153.600004
-    2     512.0  655.360017      585.142849   154.566038
-    3     640.0  682.666684      640.000002   158.759699
+    2     512.0  655.360017      606.814814   154.566038
+    3     640.0  706.206879      640.000002   160.000000
     4     768.0  722.823517      664.216187   162.754967
     ..      ...         ...             ...          ...
-    93  12160.0  812.359066      406.179533   198.834951
-    94  12288.0  812.429770      415.661740   199.197579
-    95  12416.0  812.498981      412.149375   198.805107
-    96  12544.0  812.566838      412.546756   199.111113
-    97  12672.0  811.007961      412.097543   199.167004
+    93  12160.0  812.359066      406.179533   198.429370
+    94  12288.0  812.429770      415.661740   198.794749
+    95  12416.0  812.498981      412.149375   198.358474
+    96  12544.0  812.566838      412.546756   198.716830
+    97  12672.0  812.633240      412.097543   198.776477
 
     [98 rows x 4 columns]
 
@@ -306,7 +306,7 @@ In the above plot, we can see that:
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 3 minutes  19.837 seconds)
+   **Total running time of the script:** ( 3 minutes  13.971 seconds)
 
 
 .. _sphx_glr_download_getting-started_tutorials_02-fused-softmax.py:

master/_sources/getting-started/tutorials/03-matrix-multiplication.rst.txt

@@ -459,37 +459,37 @@ We can now compare the performance of our kernel against that of cuBLAS. Here we
 
     matmul-performance:
              M     cuBLAS  ...     Triton  Triton (+ LeakyReLU)
-    0    256.0   2.730667  ...   3.276800              2.978909
-    1    384.0   7.372800  ...   7.899428              7.899428
-    2    512.0  14.563555  ...  15.420235             15.420235
+    0    256.0   2.730667  ...   3.276800              3.276800
+    1    384.0   7.372800  ...   8.507077              8.507077
+    2    512.0  14.563555  ...  15.887515             15.420235
     3    640.0  22.260869  ...  24.380953             24.380953
-    4    768.0  32.768000  ...  34.028308             34.028308
-    5    896.0  37.971025  ...  40.140799             39.025776
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+    5    896.0  39.025776  ...  41.321411             39.025776
     6   1024.0  49.932191  ...  53.773130             52.428801
     7   1152.0  45.242181  ...  48.161033             47.396572
     8   1280.0  51.200001  ...  57.690139             57.690139
     9   1408.0  64.138541  ...  68.147202             67.305878
     10  1536.0  79.526831  ...  80.430545             78.643199
-    11  1664.0  62.929456  ...  63.372618             62.061463
-    12  1792.0  72.983276  ...  63.142831             62.790080
-    13  1920.0  69.120002  ...  71.257735             70.892307
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+    12  1792.0  72.983276  ...  63.499573             63.142831
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     14  2048.0  73.262953  ...  78.033565             76.959706
-    15  2176.0  83.155572  ...  87.494120             85.998493
-    16  2304.0  68.643310  ...  78.064941             76.809875
-    17  2432.0  71.125224  ...  75.320281             74.521127
-    18  2560.0  77.833728  ...  82.539044             81.715711
-    19  2688.0  84.295681  ...  90.966561             89.254248
-    20  2816.0  82.838003  ...  83.873477             83.392363
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-    22  3072.0  81.589488  ...  88.473602             88.197981
-    23  3200.0  84.099871  ...  96.096095             95.238096
-    24  3328.0  83.905938  ...  82.088138             85.297742
-    25  3456.0  82.519518  ...  92.244355             92.244355
-    26  3584.0  86.457107  ...  91.377427             97.311031
-    27  3712.0  85.675250  ...  84.053300             87.246590
-    28  3840.0  83.465663  ...  88.971840             89.403396
-    29  3968.0  89.855624  ...  92.512459             87.723894
-    30  4096.0  93.891376  ...  94.187878             91.553703
+    15  2176.0  83.155572  ...  87.115360             85.632545
+    16  2304.0  68.446623  ...  78.064941             76.809875
+    17  2432.0  71.125224  ...  75.522751             74.521127
+    18  2560.0  77.833728  ...  82.125311             81.512437
+    19  2688.0  83.737433  ...  90.102270             90.102270
+    20  2816.0  79.733474  ...  84.523664             82.916747
+    21  2944.0  81.967162  ...  83.758038             83.758038
+    22  3072.0  81.707223  ...  89.451983             87.924073
+    23  3200.0  84.321474  ...  93.023256             95.167286
+    24  3328.0  83.516586  ...  85.806075             86.011103
+    25  3456.0  82.519518  ...  92.297157             91.407671
+    26  3584.0  85.552231  ...  91.467482             98.268190
+    27  3712.0  85.675250  ...  88.876645             87.399253
+    28  3840.0  83.528704  ...  89.403396             87.424508
+    29  3968.0  88.040360  ...  87.976885             90.388098
+    30  4096.0  86.592080  ...  90.260743             93.401342
 
     [31 rows x 5 columns]
 
@@ -499,7 +499,7 @@ We can now compare the performance of our kernel against that of cuBLAS. Here we
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 6 minutes  0.141 seconds)
+   **Total running time of the script:** ( 5 minutes  41.088 seconds)
 
 
 .. _sphx_glr_download_getting-started_tutorials_03-matrix-multiplication.py:

master/_sources/getting-started/tutorials/04-low-memory-dropout.rst.txt

@@ -240,7 +240,7 @@ References
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 0 minutes  0.493 seconds)
+   **Total running time of the script:** ( 0 minutes  0.548 seconds)
 
 
 .. _sphx_glr_download_getting-started_tutorials_04-low-memory-dropout.py:

master/_sources/getting-started/tutorials/05-layer-norm.rst.txt

@@ -42,25 +42,25 @@ Layer Normalization
     1    1536.0  630.153868  323.368435  511.999982
     2    2048.0  682.666643  334.367358  520.126988
     3    2560.0  694.237267  362.477870  512.000013
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+    4    3072.0  712.347810  376.643666  501.551037
     5    3584.0  725.873439  384.859062  455.111115
     6    4096.0  728.177767  381.023256  455.111095
-    7    4608.0  670.254540  394.267384  428.651163
+    7    4608.0  670.254540  396.387087  428.651163
     8    5120.0  688.403381  397.669909  422.268057
-    9    5632.0  704.000002  395.228063  415.262685
+    9    5632.0  704.000002  395.228063  417.185184
     10   6144.0  702.171410  402.885254  411.313806
-    11   6656.0  705.271522  398.861429  400.360920
+    11   6656.0  705.271522  400.360920  400.360920
     12   7168.0  690.891575  396.844306  387.459443
-    13   7680.0  682.666656  392.587863  387.634072
-    14   8192.0  636.271854  392.431125  371.308771
+    13   7680.0  682.666656  392.587863  386.415087
+    14   8192.0  639.375598  393.609605  371.308771
     15   8704.0  630.153861  389.005597  380.502740
     16   9216.0  609.322328  407.337026  383.999986
     17   9728.0  589.575753  409.599987  383.369452
-    18  10240.0  568.888869  408.578556  382.803739
+    18  10240.0  568.888869  408.578556  381.911416
     19  10752.0  551.384634  411.559798  381.445676
     20  11264.0  536.380957  406.826188  373.134567
-    21  11776.0  523.377770  409.599991  377.587162
-    22  12288.0  517.389457  413.911572  382.505826
+    21  11776.0  524.835658  409.599991  377.587162
+    22  12288.0  517.389457  413.911572  383.251457
     23  12800.0  505.679014  410.420828  376.470582
     24  13312.0  494.180982  405.699062  376.310952
     25  13824.0  482.934503  411.888257  379.389355
@@ -389,7 +389,7 @@ Layer Normalization
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 5 minutes  19.504 seconds)
+   **Total running time of the script:** ( 5 minutes  12.730 seconds)
 
 
 .. _sphx_glr_download_getting-started_tutorials_05-layer-norm.py:

master/_sources/getting-started/tutorials/sg_execution_times.rst.txt

@@ -5,16 +5,16 @@
 
 Computation times
 =================
-**16:22.439** total execution time for **getting-started_tutorials** files:
+**15:35.109** total execution time for **getting-started_tutorials** files:
 
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 06:00.141 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 05:41.088 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_05-layer-norm.py` (``05-layer-norm.py``)                       | 05:19.504 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_05-layer-norm.py` (``05-layer-norm.py``)                       | 05:12.730 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``)                 | 03:19.837 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``)                 | 03:13.971 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``)                       | 01:42.464 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``)                       | 01:26.773 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_getting-started_tutorials_04-low-memory-dropout.py` (``04-low-memory-dropout.py``)       | 00:00.493 | 0.0 MB |
+| :ref:`sphx_glr_getting-started_tutorials_04-low-memory-dropout.py` (``04-low-memory-dropout.py``)       | 00:00.548 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------+-----------+--------+

master/getting-started/tutorials/01-vector-add.html

@@ -325,22 +325,22 @@ for different problem sizes.</p>
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 1        8192.0   19.200000   19.200000
 2       16384.0   38.400001   38.400001
-3       32768.0   76.800002   63.999998
+3       32768.0   76.800002   76.800002
 4       65536.0  127.999995  127.999995
 5      131072.0  219.428568  219.428568
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 7      524288.0  472.615390  472.615390
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-9     2097152.0  722.823517  702.171410
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-13   33554432.0  842.004273  842.004273
+13   33554432.0  842.004273  842.906750
 14   67108864.0  847.448255  848.362445
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 </pre></div>
 </div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  42.464 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes  26.773 seconds)</p>
 <div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-getting-started-tutorials-01-vector-add-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
 <p><a class="reference download internal" download="" href="../../_downloads/62d97d49a32414049819dd8bb8378080/01-vector-add.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">01-vector-add.py</span></code></a></p>

master/getting-started/tutorials/02-fused-softmax.html

@@ -369,17 +369,17 @@ We will then compare its performance against (1) <code class="code docutils lite
 <p class="sphx-glr-script-out">Out:</p>
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>softmax-performance:
           N      Triton  Torch (native)  Torch (jit)
-0     256.0  512.000001      512.000001   186.181817
+0     256.0  546.133347      512.000001   188.321838
 1     384.0  614.400016      585.142862   153.600004
-2     512.0  655.360017      585.142849   154.566038
-3     640.0  682.666684      640.000002   158.759699
+2     512.0  655.360017      606.814814   154.566038
+3     640.0  706.206879      640.000002   160.000000
 4     768.0  722.823517      664.216187   162.754967
 ..      ...         ...             ...          ...
-93  12160.0  812.359066      406.179533   198.834951
-94  12288.0  812.429770      415.661740   199.197579
-95  12416.0  812.498981      412.149375   198.805107
-96  12544.0  812.566838      412.546756   199.111113
-97  12672.0  811.007961      412.097543   199.167004
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+95  12416.0  812.498981      412.149375   198.358474
+96  12544.0  812.566838      412.546756   198.716830
+97  12672.0  812.633240      412.097543   198.776477
 
 [98 rows x 4 columns]
 </pre></div>
@@ -392,7 +392,7 @@ We will then compare its performance against (1) <code class="code docutils lite
 Note however that the PyTorch <cite>softmax</cite> operation is more general and will works on tensors of any shape.</p></li>
 </ul>
 </div></blockquote>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes  19.837 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes  13.971 seconds)</p>
 <div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-getting-started-tutorials-02-fused-softmax-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
 <p><a class="reference download internal" download="" href="../../_downloads/d91442ac2982c4e0cc3ab0f43534afbc/02-fused-softmax.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">02-fused-softmax.py</span></code></a></p>

master/getting-started/tutorials/03-matrix-multiplication.html

@@ -565,42 +565,42 @@ torch_output=tensor([[  1.1045, -36.9688,  31.4688,  ..., -11.3906,  24.4531, -3
 <p class="sphx-glr-script-out">Out:</p>
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>matmul-performance:
          M     cuBLAS  ...     Triton  Triton (+ LeakyReLU)
-0    256.0   2.730667  ...   3.276800              2.978909
-1    384.0   7.372800  ...   7.899428              7.899428
-2    512.0  14.563555  ...  15.420235             15.420235
+0    256.0   2.730667  ...   3.276800              3.276800
+1    384.0   7.372800  ...   8.507077              8.507077
+2    512.0  14.563555  ...  15.887515             15.420235
 3    640.0  22.260869  ...  24.380953             24.380953
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+4    768.0  32.768000  ...  35.389441             34.028308
+5    896.0  39.025776  ...  41.321411             39.025776
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 7   1152.0  45.242181  ...  48.161033             47.396572
 8   1280.0  51.200001  ...  57.690139             57.690139
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-25  3456.0  82.519518  ...  92.244355             92.244355
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-27  3712.0  85.675250  ...  84.053300             87.246590
-28  3840.0  83.465663  ...  88.971840             89.403396
-29  3968.0  89.855624  ...  92.512459             87.723894
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+15  2176.0  83.155572  ...  87.115360             85.632545
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+17  2432.0  71.125224  ...  75.522751             74.521127
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